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Code clone detection using coarse and fine-grained hybrid approaches

机译:使用粗粒度和细粒度混合方法进行代码克隆检测

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摘要

If two fragments of source code are identical to each other, they are called code clones. Code clones introduce difficulties in software maintenance and cause bug propagation. Coarse-grained clone detectors have higher precision than fine-grained, but fine-grained detectors have higher recall than coarse-grained. In this paper, we present a hybrid clone detection technique that first uses a coarse-grained technique to analyze clones effectively to improve precision. Subsequently, we use a fine-grained detector to obtain additional information about the clones and to improve recall. Our method detects Type-1 and Type-2 clones using hash values for blocks, and gapped code clones (Type-3) using block detection and subsequent comparison between them using Levenshtein distance and Cosine measures with varying thresholds.
机译:如果源代码的两个片段彼此相同,则将它们称为代码克隆。代码克隆会给软件维护带来困难,并导致错误传播。粗粒度克隆检测器的精度高于细粒度,但细粒度检测器的召回率高于粗粒度。在本文中,我们提出了一种混合克隆检测技术,该技术首先使用粗粒度技术有效地分析克隆以提高精度。随后,我们使用细粒度检测器获得有关克隆的其他信息并提高召回率。我们的方法使用块的哈希值检测类型1和类型2的克隆,并使用块检测来检测带间隙的代码克隆(类型3),并随后使用Levenshtein距离和具有不同阈值的余弦量度在它们之间进行比较。

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